A Whole-Body Motion Imitation Framework from Human Data for Full-Size Humanoid Robot
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arXiv
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| Main Authors: | , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866918109731880960 |
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| author | Chen, Zhenghan Zhang, Haodong Wang, Dongqi Yu, Jiyu Xu, Haocheng Wang, Yue Xiong, Rong |
| author_facet | Chen, Zhenghan Zhang, Haodong Wang, Dongqi Yu, Jiyu Xu, Haocheng Wang, Yue Xiong, Rong |
| contents | Motion imitation is a pivotal and effective approach for humanoid robots to achieve a more diverse range of complex and expressive movements, making their performances more human-like. However, the significant differences in kinematics and dynamics between humanoid robots and humans present a major challenge in accurately imitating motion while maintaining balance. In this paper, we propose a novel whole-body motion imitation framework for a full-size humanoid robot. The proposed method employs contact-aware whole-body motion retargeting to mimic human motion and provide initial values for reference trajectories, and the non-linear centroidal model predictive controller ensures the motion accuracy while maintaining balance and overcoming external disturbances in real time. The assistance of the whole-body controller allows for more precise torque control. Experiments have been conducted to imitate a variety of human motions both in simulation and in a real-world humanoid robot. These experiments demonstrate the capability of performing with accuracy and adaptability, which validates the effectiveness of our approach. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2508_00362 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | A Whole-Body Motion Imitation Framework from Human Data for Full-Size Humanoid Robot Chen, Zhenghan Zhang, Haodong Wang, Dongqi Yu, Jiyu Xu, Haocheng Wang, Yue Xiong, Rong Robotics Motion imitation is a pivotal and effective approach for humanoid robots to achieve a more diverse range of complex and expressive movements, making their performances more human-like. However, the significant differences in kinematics and dynamics between humanoid robots and humans present a major challenge in accurately imitating motion while maintaining balance. In this paper, we propose a novel whole-body motion imitation framework for a full-size humanoid robot. The proposed method employs contact-aware whole-body motion retargeting to mimic human motion and provide initial values for reference trajectories, and the non-linear centroidal model predictive controller ensures the motion accuracy while maintaining balance and overcoming external disturbances in real time. The assistance of the whole-body controller allows for more precise torque control. Experiments have been conducted to imitate a variety of human motions both in simulation and in a real-world humanoid robot. These experiments demonstrate the capability of performing with accuracy and adaptability, which validates the effectiveness of our approach. |
| title | A Whole-Body Motion Imitation Framework from Human Data for Full-Size Humanoid Robot |
| topic | Robotics |
| url | https://arxiv.org/abs/2508.00362 |